Barriers and Facilitators to Accessing Rural Nursing Education in Canada: A Scoping Review
Bibliographic record
Abstract
Rural Canadian nurses are vital to safe and competent healthcare. Access to educational opportunities meets nurses' professional and personal needs. This scoping review examines the barriers and facilitators that affect rural Canadian Licensed Practical Nurses (LPNs)/Registered Practical Nurses (RPrN), Registered Nurses (RNs), Registered Psychiatric Nurses (RPNs), and Nurse Practitioners (NPs) in accessing and engaging in educational opportunities for career advancement and practicing with an expanded scope. These barriers and facilitators will be examined from personal, agency, educational institution, and regulatory perspectives. Using a JBI approach design, this scoping review will evaluate peer-reviewed published primary research studies. Sources from 2014-2024 and in English that reflect aspects of the research objectives will be included. Two reviewers will independently screen sources at the title, abstract, and full-screen phases. Data will be extracted using Covidence, and the team will follow the JBI charting methods while using the data extraction tool. Findings will present the depth and breadth of knowledge, summarizing the characteristics of the sources and body of literature and discussing themes related to barriers and facilitators of educational opportunities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.028 | 0.091 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.028 | 0.047 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".